报告题目：智能空间转录组学：为破译组织结构铺平道路
主讲人：张世华
主讲人单位：中国科学院数学与系统科学研究院
报告摘要:
Technological advances in spatial transcriptomics are critical for a better understanding of the structure and function of tissues in biological research. Recently, the combination of intelligent/statistical algorithms and spatial transcriptomics are emerging to pave the way for deciphering tissue architecture. In this talk, I will introduce our efforts to advance intelligent spatial transcriptomics. We first develop a graph attention auto-encoder framework STAGATE to accurately identify spatial domains by learning low-dimensional latent embeddings via integrating spatial information and gene expression profiles. We validate STAGATE on diverse spatial transcriptomics datasets generated by different platforms with different spatial resolutions. STAGATE could substantially improve the identification accuracy of spatial domains, and denoise the data while preserving spatial expression patterns. Importantly, STAGATE could be extended to multiple consecutive sections to reduce batch effects between sections and extracting three-dimensional (3D) expression domains from the reconstructed 3D tissue effectively. Based on this, we 1) develop STAMarker for identifying spatial domain-specific variable genes, 2) design STAligner for integrating spatial transcriptomics of multiple slices from diverse biological scenarios, and 3) illustrate the effectiveness of the graph attention auto-encoder for spatial clustering of spatial metabolomics.
个人简介：
张世华，中国科学院数学与系统科学研究院研究员、中国科学院随机复杂结构与数据科学重点实验室副主任、中国科学院大学岗位教授。主要从事生物信息计算、机器智能与优化交叉研究，主要成果发表在Cell、Nature Communications、Advanced Science、Cell Reports、National Science Review、Science Bulletin、Nucleic Acids Research、IEEE TPAMI、IEEE TKDE、IEEE TNNLS等杂志。曾荣获中国科学院院长特别奖(2008)、全国百篇优秀博士论文奖（2010）、中国青年科技奖(2013）、中国科学院卢嘉锡青年人才奖(2013）、教育部自然科学二等奖(排名第三)(2018)、中创软件人才奖(2022)等。先后获得国家自然科学基金优秀青年基金(2014)、中国科学院卓越青年科学家项目(2014)、国家万人计划青年拔尖人才(2018)、中国科学院稳定支持基础研究领域青年团队计划(2022)等资助。成果入选2021年度中国生物信息学十大进展、2019年度中国生物信息学十大算法和工具。现任PLOS Computational Biology和BMC Genomics等杂志编委。
报告时间：2022年9月22日（星期四）上午10:00-11:00
报告地点：腾讯会议：627-600-620
